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The present study intends to foster understanding of how a traditional manufacturer can utilize the “simple rules” approach of managerial heuristics to facilitate its smart solution development (SSD) process.

The study uses an in-depth single case research strategy and 25 senior manager interviews to understand the application of simple rules in smart solution development.

The findings reveal process, boundary, preference, schedule, and stop rules as the dominant managerial heuristics in the case and identify how the manufacturer applies these rules during the innovation process phases of ideation, incubation, transformation, and industrialization for attaining project outcomes.

The study contributes to the new service development (NSD) literature by shedding light on simple rules and how managers may apply them to facilitate SSD. The main limitations stem from applying the qualitative case study approach and the interpretative nature of the study, which produces novel insights but prevents direct generalization to other empirical cases.

The resulting framework provides guidelines for managers on how to establish formal and clear simple rules that enable industrial solution providers to approach decision-making in smart solution development in a more agile manner.

The study comprises one of the first attempts to investigate managerial heuristics in the context of SSD and puts forward a plea for further NSD research applying psychological conceptualizations to enrich the simple rules perspective.

This article aims to provide a theoretical unifying framework for flexible organizational forms, such as so-called adhocracies and network organizations.

In this article, organization practices that are typical of the software industry are analyzed and re-interpreted by means of foundational concepts of organization science. It is shown that one and the same logic is at work in all flexible organizations.

Coordination modes can be fruitfully employed to characterize flexible organizations. In particular, standardization is key in order to obtain flexibility, provided that a novel sort of coordination by standardization is added to those that have been conceptualized hitherto.

This article highlights one necessary condition for organizations to be flexible. Further aspects, only cursorily mentioned in this paper, need to be addressed in order to obtain a complete picture.

A theory of organizational flexibility constitutes a guide for organizational design. This article suggests the non-obvious prescription that the boundary conditions of individual behavior must be standardized in order to achieve operational flexibility.

This theoretical framework can be profitably employed in management classes.

Currently, flexible organizations are only understood in terms of lists of instances. This article shows that apparently heterogeneous case-studies share common features in fact.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

There is a certain error in the satellite positioning of the vehicle. The error will cause the drift point of the positioning point, which makes the vehicle trajectory shift to the real road. This paper aims to solve this problem.

The key technology to solve the problem is map matching (MM). The low sampling frequency of the vehicle is far from the distance between adjacent points, which weakens the correlation between the points, making MM more difficult. In this paper, an MM algorithm based on priority rules is designed for vehicle trajectory characteristics at low sampling frequencies.

The experimental results show that the MM based on priority rule algorithm can effectively match the trajectory data of low sampling frequency with the actual road, and the matching accuracy is better than other similar algorithms, the processing speed reaches 73 per second.

In the algorithm verification of this paper, although the algorithm design and experimental verification are considered considering the diversity of GPS data sampling frequency, the experimental data used are still a single source.

Based on the GPS trajectory data of the Ministry of Transport, the experimental results show that the accuracy of the priority-based weight-based algorithm is higher. The accuracy of this algorithm is over 98.1 per cent, which is better than other similar algorithms.

This paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.

From a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.

The authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.

The authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.

The purpose of this paper is to focus on the reference model of a grid-like supply network that enables formulation of delivery routing and scheduling problems in the context of the periodic vehicle routing problem.

The conditions for seamless (collision-free) synchronization of periodically executed local transport processes presented in this paper guarantee cyclic execution of supply processes, thereby preventing traffic flow congestion.

Systems that satisfy this characteristic, cyclic deliveries executed along supply chains are given and what is sought is the number of vehicles needed to operate the local transport processes in order to ensure delivery from and to specific loading/unloading points on given dates. Determination of sufficient conditions guaranteeing the existence of feasible solutions that satisfy these constraints makes it possible to solve the considered class of problems online.

The computer experiments reported in this paper show the possibilities of practical application of the proposed approach in the construction of decision support systems for food supply chain management.

The aim of the present work is to develop a methodology for the synthesis of regularly structured supply networks that would ensure fixed cyclic execution of local transport processes. The proposed methodology, which implements sufficient conditions for the synchronization of local cyclic processes, allows one to develop a method for rapid prototyping of supply processes that satisfies the time windows constraints given.

Cybersecurity in healthcare has become an urgent matter in recent years due to various malicious attacks on hospitals and other parts of the healthcare infrastructure. The purpose of this paper is to provide an outline of how core values of the health systems, such as the principles of biomedical ethics, are in a supportive or conflicting relation to cybersecurity.

This paper claims that it is possible to map the desiderata relevant to cybersecurity onto the four principles of medical ethics, i.e. beneficence, non-maleficence, autonomy and justice, and explore value conflicts in that way.

With respect to the question of how these principles should be balanced, there are reasons to think that the priority of autonomy relative to beneficence and non-maleficence in contemporary medical ethics could be extended to value conflicts in health-related cybersecurity.

However, the tension between autonomy and justice, which relates to the desideratum of usability of information and communication technology systems, cannot be ignored even if one assumes that respect for autonomy should take priority over other moral concerns.

In terms of value conflicts, most discussions in healthcare deal with the conflict of balancing efficiency and privacy given the sensible nature of health information. In this paper, the authors provide a broader and more detailed outline.